1. Field of the Invention
In at least one aspect, the present invention is related to an improved video surveillance system.
2. Background Art
Increasing security concerns have provided an impetus for improved video surveillance systems. Security problems have emerged as a major concern regionally, nationally, and globally. Therefore, the interest in video surveillance has grown dramatically. Currently, video surveillance systems are primarily used as a deterrent and a forensic tool.
Recent advances in networking, video sensors, and networked video cameras have enabled the development of large-scale surveillance systems. Some organizations use video surveillance to facilitate real-time detection of suspicious activities. Some of the larger surveillance systems currently being deployed consist of hundreds or millions of cameras distributed over a wide area. These cameras are usually connected to a central monitoring location that is observed by trained personnel. Beside the prohibitive cost of such systems, many critical events may be undetected because humans cannot simultaneously monitor an arbitrarily large number of cameras. Automated video surveillance systems provide one solution to this problem. Such systems typically employ smart computer vision algorithms to detect suspicious activities and events. Automated video surveillance serves as an elegant and efficient approach for real-time detection of threats and for monitoring their progress and the effectiveness of any countermeasures.
The design of an automated, scalable, and massively distributed surveillance system has become a significant research endeavor. Many prior art surveillance systems focus on developing robust vision algorithms for the detection, tracking, and classification of objects and events. A relatively insignificant effort has been devoted to improving scalability and costs of video surveillance systems. The scalability-cost problem arises because increasing the coverage through employing additional video sources (i.e., networked cameras or video sensors) leads to increasing both the required bandwidth and the computational power to process all these video streams.
Accordingly, there is a need for improved technology for video surveillance systems.